Abstract
This paper proposes a novel fermentation control method. Two stages are involved. First, propose the fermentation time model and the optimal fermentation temperature model based on RBF Neural networks. Second, on the base of the two models, propose the novel fermentation control method by which different fermentation batch can adopt different optimal fermentation temperature trajectory which fits itself. Using this method, each fermentation batch can be fermented at optimal fermentation temperature trajectory and will improve average product proportion. The practical application showed that this method can improve average product proportion 3% effectively.
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© 2004 Springer-Verlag Berlin Heidelberg
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Yang, X., Sun, Z., Sun, Y. (2004). A Novel Fermentation Control Method Based on Neural Networks. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_30
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DOI: https://doi.org/10.1007/978-3-540-28648-6_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
eBook Packages: Springer Book Archive